Forkhead box C1 (FOXC1) is a transcription factor with essential roles in mesenchymal lineage specification and organ development during normal embryogenesis. In keeping with these developmental properties, mutations that impair the activity of FOXC1 result in the heritable Axenfeld-Rieger Syndrome and other congenital disorders. Crucially, gain of FOXC1 function is emerging as a recurrent feature of malignancy; FOXC1 overexpression is now documented in more than 16 cancer types, often in association with an unfavorable prognosis. This review explores current evidence for FOXC1 deregulation in cancer and the putative mechanisms by which FOXC1 confers its oncogenic effects.

Acute myeloid leukemia (AML) is a heterogeneous disease caused by a variety of alterations in transcription factors, epigenetic regulators and signaling molecules. To determine how different mutant regulators establish AML subtype-specific transcriptional networks, we performed a comprehensive global analysis of cis-regulatory element activity and interaction, transcription factor occupancy and gene expression patterns in purified leukemic blast cells. Here, we focused on specific subgroups of subjects carrying mutations in genes encoding transcription factors (RUNX1, CEBPα), signaling molecules (FTL3-ITD, RAS) and the nuclear protein NPM1). Integrated analysis of these data demonstrates that each mutant regulator establishes a specific transcriptional and signaling network unrelated to that seen in normal cells, sustaining the expression of unique sets of genes required for AML growth and maintenance.

Immunological memory is a defining feature of vertebrate physiology, allowing rapid responses to repeat infections. However, the molecular mechanisms required for its establishment and maintenance remain poorly understood. Here, we demonstrated that the first steps in the acquisition of T‐cell memory occurred during the initial activation phase of naïve T cells by an antigenic stimulus. This event initiated extensive chromatin remodeling that reprogrammed immune response genes toward a stably maintained primed state, prior to terminal differentiation. Activation induced the transcription factors NFAT and AP ‐1 which created thousands of new DN ase I‐hypersensitive sites ( DHS s), enabling ETS ‐1 and RUNX 1 recruitment to previously inaccessible sites. Significantly, these DHS s remained stable long after activation ceased, were preserved following replication, and were maintained in memory‐phenotype cells. We show that primed DHS s maintain regions of active chromatin in the vicinity of inducible genes and enhancers that regulate immune responses. We suggest that this priming mechanism may contribute to immunological memory in T cells by facilitating the induction of nearby inducible regulatory elements in previously activated T cells.

The Drosophila larva possesses just 21 unique and identifiable pairs of olfactory sensory neurons (OSNs), enabling investigation of the contribution of individual OSN classes to the peripheral olfactory code. We combined electrophysiological and computational modeling to explore the nature of the peripheral olfactory code in situ. We recorded firing responses of 19/21 OSNs to a panel of 19 odors. This was achieved by creating larvae expressing just one functioning class of odorant receptor, and hence OSN. Odor response profiles of each OSN class were highly specific and unique. However many OSN-odor pairs yielded variable responses, some of which were statistically indistinguishable from background activity. We used these electrophysiological data, incorporating both responses and spontaneous firing activity, to develop a bayesian decoding model of olfactory processing. The model was able to accurately predict odor identity from raw OSN responses; prediction accuracy ranged from 12%-77% (mean for all odors 45.2%) but was always significantly above chance (5.6%). However, there was no correlation between prediction accuracy for a given odor and the strength of responses of wild-type larvae to the same odor in a behavioral assay. We also used the model to predict the ability of the code to discriminate between pairs of odors. Some of these predictions were supported in a behavioral discrimination (masking) assay but others were not. We conclude that our model of the peripheral code represents basic features of odor detection and discrimination, yielding insights into the information available to higher processing structures in the brain.